[PDF] Top 20 Novel Algorithm to Reduced Computational Data Sets for Fuzzy Association Rule
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Novel Algorithm to Reduced Computational Data Sets for Fuzzy Association Rule
... day’s fuzzy logic and data mining are the two most important techniques on the field of research ...area. Fuzzy logic uses linguistic variable to provide the answer that human being are unable to ... See full document
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Performance of Novel Based Fuzzy Association Rules to Reduced Computational Data Sets by Row Counts
... large data sets ...a novel algorithm to reduce the large data sets to smaller one without affecting the result of fuzzy association rule by Row count ...the ... See full document
7
Pseudo Code to Eliminate Unwanted Data Sets for Fuzzy Mining Association Rule
... that data mining association rule is very easy for small or medium data ...apply fuzzy association rule then it will be a complex task for large data ...the ... See full document
6
Fuzzy Association Rule by Classification Technique
... day’s fuzzy logic and data mining are the two most important techniques on the field of research ...area. Fuzzy logic uses linguistic variable to provide the answer that human being are not able to ... See full document
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THE COMPARATIVE ANALYSIS OF ROAD ACCIDENT DATA USING DATA MINING TECHNIQUES Dr. B.G.Geetha 1, Abinaya.N2 , Abirami Sivasakthi.M 3 Aishwarya.T 4
... Association rule mining is a popular data mining technique that is based on market basket data ...used association rule mining using Apriori algorithm for road accident ... See full document
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EFFECTIVE SECURE MINING OF ASSOCIATION RULE WITH SUBGROUP DISCOVERY IN HORIZONTALLY DISTRIBUTED DATABASES
... Item sets— Kantarcioglu and Clifton) is based on the Fast Distributed Mining (FDM) Algorithm which is an unsecured distributed version of the Apriori algorithm ...two novel secure multi-party ... See full document
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Secured Association Rule Mining In Partitioned Database
... a novel and a flexible framework called mobile-agent-based distributed algorithm for association rules (IDMA) with aim of to mine the global and local large itemsets at the same ...incremental ... See full document
8
SARM: An Approach for the Analysis of Association Rule using SVM Classification Technique
... an algorithm for building ontology via set of rules generated by rule based learning ...This algorithm has extracted the rules generated from the original dataset in developing ontology ...of ... See full document
5
Exploration of Novel Algorithm for Reduced Computational Time by Using Fuzzy Classification Technique in Data Mining
... unwanted data sets from large data sets. We apply fuzzy logic , classification and data mining techniques to do the ...of data items is very large, so it is difficult to ... See full document
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Prediction of Data Sets by using Fuzzy Mining Association Rule
... In this section, the fusion model is proposed to improve the persuasiveness in determining the universe of discourse and membership functions of fuzzy association rules. Firstly, we build the membership ... See full document
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IMPROVING APRIORI ALGORITHM USING PAFI AND TDFI
... of Association rules in huge database is the challenging and tough ...this Association an Apriori algorithm is mostly ...Apriori algorithm is to find out the frequent item sets from ... See full document
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Association Rule Granulation using Rough Sets on Intuitionistic Fuzzy Approximation Spaces and Granular Computing
... individual data element or pattern of data elements may change dramatically from individual to individual, organization to organization, or task to task because of the acquisition of knowledge and reasoning ... See full document
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Privacy Preserving Association Rule Mining using ROBFRUGHAL Algorithm
... the data to be partitioned in order to secure the data according to the privacy concerns of the data ...the data owner has one or more rows in the joint database then that database is called ... See full document
6
Mining Multilevel Fuzzy Association Rule from Transaction Data
... defined fuzzy set concepts, multiple level taxonomy and different minimum supports for each level and find fuzzy association rules in a given transaction data ...The algorithm works ... See full document
6
Evaluation of machine learning techniques for imbalanced data in IDS
... in data mining community and a number of solutions have been proposed at the data and algorithm levels and trying to address the imbalanced data ...imbalanced data is not properly ... See full document
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Multilevel Index Algorithm Based on Improved Association Rule Mining
... improved association rule mining algorithm using multi index database, frequent item sets of association rules produce the desired set of features, the feature sub space narrowing of ... See full document
9
Tree Approach To Mine Frequent Pattern In Association Using Apriori Algorithm
... We propose two new methods for mining frequent itemsets in parallel on the MapReduce framework where frequency thresholds can be set low. Our first method, called Dist-Eclat, is a pure Eclat method that distributes the ... See full document
6
Fuzzy Neuro Model for Intelligent Credit Risk Management
... The test samples, TE, on the other hand, were classi- fied by the system as having patterns much similar with EV. But the graph in Figure 9 shows that the TE samples have more patterns that are diverse than that of EV ... See full document
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A quantifier based fuzzy classification system for breast cancer patients
... While 25 protein markers were originally used to derive the biological tumour classes presented by Soria et al. [21], this was subsequently reduced down to the above mentioned ten as the minimum number of markers ... See full document
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Abstract: Data mining discovers hidden pattern in data sets and association between the patterns. In this association rule
... An occurrence counter and a pointer to the sorted transaction (array of contained items). This data structure is then processed recursively to find the frequent item sets. The basic operations of the ... See full document
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